The Fuzzy Text Search API finds close matches for user queries, handling typos and partial inputs to deliver relevant results quickly and accurately.
The Fuzzy Text Search API, hosted on ApyHub, compares a search term against a space-separated target string and returns the matching words as an array of strings. It accepts source and target values in the request body, with optional accent-insensitive and unicode-normalized query string parameters (both boolean, default false) to control how comparisons handle accented characters and differing encodings.
The API is intended for tolerant string matching rather than exact comparison, such as checking whether a user-entered fragment matches words in a title, product name, or other free-text field. The response is a JSON object containing a data array of matched strings.
It is a single POST endpoint (version 1.0), suited for integration into autocomplete, filtering, suggestion systems, and content review pipelines. Standard error responses include 400 for missing or malformed request bodies, 401 for missing or unauthorized API keys, 429 for rate limiting, and 503 for temporary backend unavailability.
It compares a source search term against a space-separated target string and returns the matching words as an array of strings.
Send a POST request with source and target fields in the JSON body, authenticated with an apy-token header.
Yes, you can set accent-insensitive and unicode-normalized query string flags, both defaulting to false.
It returns a JSON object with a data array containing the matching words found in the target string.
It is published and hosted by ApyHub as a verified, listed API, currently at version 1.0.
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